Determining settings of a camera apparatus

ABSTRACT

Methods and computer program products for determining one or more settings of a camera apparatus are provided. The methods include obtaining one or more parameters of the camera apparatus and determining one or more settings of the camera apparatus using the one or more parameters and an image repository. The image repository may include images with image parameters associated with the images, which may be correlated with the one or more parameters of the camera apparatus, and the images may also have an associated rating attribute. One or more images may be identified for inclusion in a subset of images, based on an image&#39;s image parameters and/or based on an image&#39;s rating attribute. The camera settings of one image of the subset of images, corresponding to the settings used to create the one image, may be used to automatically adjust the one or more settings of the camera apparatus.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.14/826,693, filed Aug. 14, 2015, entitled, “Determining Settings of aCamera Apparatus,” the entirety of which is hereby incorporated hereinby reference.

TECHNICAL FIELD

The present disclosure relates to determining settings of a cameraapparatus, and more particularly to determining settings of a cameraapparatus using parameters of the camera apparatus and an imagerepository.

BACKGROUND

Taking pictures with a camera has been a common activity for decades andhas become even more common with the wide availability of cameras aswell as mobile devices that include a camera apparatus embedded orintegrated into the device. Taking professional quality images, however,remains a challenge. Professional as well as amateur photographers mayfind it difficult to manually determine what camera settings are best inany particular situation, not only due to variable external conditionssuch as lighting and weather but also due to the complex interplay ofcamera settings and components.

SUMMARY

Shortcomings of the prior art are overcome and additional advantages areprovided through the provision, in one aspect, of a method. The methodincludes obtaining, at one or more processor, one or more parameters ofa camera apparatus. The method further includes determining, at one ormore processor, one or more settings of the camera apparatus using oneor more parameters of the camera apparatus and an image repository.

In one embodiment, the image repository is external from the cameraapparatus. This may, for example, provide the user of the cameraapparatus with access to image repositories stored on remote servers orthat are provided as services in a cloud environment.

In one embodiment, using the image repository includes using one or moreimages of the image repository. The one or more images have one or moreimage parameters associated with the one or more images. The determiningfurther includes identifying, at the one or more processor, acorrespondence between at least one image parameter and at least oneparameter of the one or more parameters of the camera apparatus. Thismay, for example, advantageously facilitate matching images from theimage repository to parameters of the camera apparatus to determineappropriate settings for the camera apparatus.

In another embodiment, the one or more images have a rating attribute.Using the one or more images may include identifying at least one imageof the one or more images to be included in a subset of images, theidentifying being based on the rating attribute of the at least oneimage and on at least one image parameter of the at least one image.This may, for example, help in selecting highly-rated images that werecreated with similar parameters as the camera apparatus, furtherfacilitating determining the settings for the camera apparatus.

In another embodiment, at least one image identified to be included inthe subset of images has more image parameters identified ascorresponding to parameters of the one or more parameters of the cameraapparatus than images of the one or more images not identified to beincluded in the subset of images. For example, a particular image in theimage repository may have been created with several parameters in commonwith the camera apparatus, while other images in the repository may havefew or no parameters in common with the camera apparatus. To determinethe most appropriate settings for the camera apparatus, the image withseveral parameters in common may be chosen for determining the settingsof the camera apparatus, while the other images may not be selected.

In another embodiment, the at least one image identified to be includedin the subset of images has a higher rating attribute than images of theone or more images not identified to be included in the subset ofimages. For example, a particular image in the image repository may havea very high rating, as rated by users of the image repository, which maycorrespond to the image's aesthetic qualities, technical qualities, orother qualities that appeal to the users. To determine the mostappropriate settings for the camera apparatus for creating an image ofsimilar quality, the image with a very high rating may be used whileother images of the repository with a lower rating may not be selectedfor use.

In another embodiment, the one or more images have one or more camerasettings associated with the one or more images, where the camerasettings of one image correspond to the camera settings that were usedto create that image. Determining the one or more settings for thecamera apparatus may further include selecting one image of the subsetof images. The one or more settings for the camera apparatus may beautomatically adjusted based on the one or more camera settingsassociated with the one image. This advantageously allows a user of thecamera apparatus to create images with the most appropriate camerasettings, based on the camera model and specifications, as well asexternal conditions, without having to know what the most appropriatesettings are for the camera and current conditions. Camera users cancreate high quality images without having to be photographyprofessionals.

In one example embodiment, selecting one image of the subset of imagesmay be performed at the one or more processor. The one image may, forinstance, have a higher rating attribute than the rating attributes ofother images included in the subset of images. For example, this allowsfor automatic selection of the most highly rated image from the imagerepository to use in determining the settings of the camera apparatus,allowing the user to create high quality images quickly and withouthaving to make manual selections.

In an alternative example embodiment, the method may include displayingthe subset of images at the camera apparatus. Selecting one image of thesubset of images may be performed by a user of the camera apparatusbased on the display of the subset of images. For example, this allowsthe user of the camera apparatus to see a subset of high quality, highlyrated images that were created using similar parameters as the user'scamera apparatus. The user may manually select one image that he or shelikes best, and that image's settings may be used to determine thesettings of the camera apparatus.

In another embodiment, the one or more settings of the camera apparatusmay include one or more of a focal length, a shutter speed, an exposuretime, a color balance, a flash setting, a light sensitivity setting, oran aperture size. For example, the image selected for use in determiningthe one or more settings of the camera apparatus may have settingsinformation regarding the shutter speed and flash settings of the camerathat was used to create the image. The settings information of the imagemay then be used to adjust the shutter speed and flash settings of thecamera apparatus to help create a similar quality image by the cameraapparatus.

In another embodiment, the one or more parameters of the cameraapparatus may include one or more of a camera brand, a camera model, animage resolution, a pixel size, a geographical location, a lightingcondition, a weather condition, a date parameter, a time parameter, acamera orientation parameter, a focal length, a shutter speed, anexposure time, a color balance, a flash setting, a light sensitivitysetting, or an aperture size. For example, it may be advantageous toselect images from the image repository that were created by a similarcamera brand and model as the user's camera apparatus, while imagescreated with different cameras may not be useful for determining thebest settings for the user's camera apparatus. In another example, ifthe camera apparatus is being used outside on a bright and clear day,then it may be advantageous to select images from the image repositorythat were also created outside on a bright and clear day, and to not useimages created in low lighting conditions or indoors.

In yet another embodiment, the image repository may be provided as aservice in a cloud environment. Providing the image repository as acloud environment may allow access to multiple images from multipleimage repositories, increasing the likelihood that high quality, highlyrated images that may be used in determining one or more settings of thecamera apparatus may be found.

In another aspect, a computer program product is provided. The computerprogram product may include a computer readable storage medium readableby one or more processing apparatus and instructions stored on thecomputer readable storage medium for execution by the one or moreprocessing apparatus. The instructions may be instructions forperforming a method that includes obtaining, at one or more processor,one or more parameters of a camera apparatus. The method furtherincludes determining, at one or more processor, one or more settings ofthe camera apparatus using one or more parameters of the cameraapparatus and an image repository.

Additional features and advantages are realized through the techniquesset forth herein. Other embodiments and aspects are described in detailherein and are considered a part of the claimed disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more aspects of the present disclosure are particularly pointedout and distinctly claimed as examples in the claims at the conclusionof the specification. The foregoing and other objects, features, andadvantages of the present disclosure are apparent from the followingdetailed description taken in conjunction with the accompanying drawingsin which:

FIG. 1 depicts a cloud computing node, in accordance with one or moreaspects set forth herein;

FIG. 2 depicts a cloud computing environment, in accordance with one ormore aspects set forth herein;

FIG. 3 depicts abstraction model layers, in accordance with one or moreaspects set forth herein;

FIGS. 4A-4B depict a hardware overview of a computing node, inaccordance with one or more aspects set forth herein;

FIG. 5 depicts a workflow, in accordance with one or more aspects setforth herein; and

FIGS. 6A-6G depict exemplary embodiments of the process depicted in FIG.5

DETAILED DESCRIPTION

Aspects of the present disclosure and certain features, advantages, anddetails thereof, are explained more fully below with reference to thenon-limiting examples illustrated in the accompanying drawings.Descriptions of well-known materials, fabrication tools, processingtechniques, etc., are omitted so as not to unnecessarily obscure thedisclosure in detail. It should be understood, however, that thedetailed description and the specific examples, while indicating aspectsdescribed herein, are given by way of illustration only, and not by wayof limitation. Various substitutions, modifications, additions, and/orarrangements, within the spirit and/or scope of the underlying conceptswill be apparent to those skilled in the art from this disclosure.

Taking pictures with a camera has become a common, given the wideavailability of stand-alone cameras, ranging from simple point-and-shootcameras to professional-level digital camera apparatuses, as well asmobile devices that include a camera apparatus embedded or integratedinto the device. Taking professional quality images, however, remains achallenge. Professional as well as amateur photographers may find itdifficult to manually determine what camera settings are best in anyparticular situation, not only due to variable external conditions suchas lighting and weather but also due to the complex interplay of camerasettings and components. The numerous settings that can affect thequality of an image may also make it difficult to determine what thebest or most appropriate settings are for any particular photographysituation.

Advantageously, the techniques presented herein provide improvedtechniques for determining one or more settings of a camera apparatus byusing one or more parameters of the camera apparatus and an imagerepository. The image repository may have a library or database ofimages that are available to users of the repository. The images mayhave image parameters associated with the images, indicating, forexample, the make or model of camera used to record an image, theambient lighting conditions or weather conditions in which the image wascreated, and so on. Camera settings may also be associated with theimages, indicating the particular settings of the camera that were usedto record an image. As well, the images in the repository may have arating attribute associated with the images, the ratings generallyassigned by users of the repository, with high ratings generallycorresponding to high-quality images. By selecting a highly-rated imagefrom the repository with image parameters that correlate to theparameters of a user's camera apparatus, the camera settings of thecamera apparatus can be automatically adjusted to match the camerasettings that were used to create the highly-rated image, enabling theuser to take similarly high-quality pictures without needing to know howto manually adjust the camera apparatus's settings for best results.

The present disclosure provides, in part, methods, computer programs,computer systems, and/or network devices that may address one or moreissues described above, and that may determine, at one or moreprocessor, one or more settings for a camera apparatus, where thedetermining includes using, by the one or more processor, one or moreparameters of the camera apparatus and an image repository.

Reference is made below to the drawings, which are not drawn to scalefor ease of understanding, wherein the same reference numbers usedthroughout different figures designate the same or similar components.

FIGS. 1-4 depict various aspects of computing, including cloudcomputing, in accordance with one or more aspects set forth herein.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and determining one or more settings of acamera apparatus 96 as described herein.

FIG. 4A depicts a hardware overview of a computing node 11, which may bea cloud computing node 10 and/or a computer system, in accordance withone or more aspects set forth herein. FIG. 4B depicts a hardwareoverview of a computing node 11 which may be a camera apparatus 25, inaccordance with one or more aspects set forth herein.

Program/utility 40 as set forth in FIG. 1 can include one or moreprogram 440 as set forth in FIG. 4A and/or FIG. 4B, and program/utility40 can optionally include some or all of one or more program 441, 442,443, 444, 445. Additionally, computer system/server 12 in FIG. 4A maycommunicate with one or more external devices 14, a display 24, and acamera apparatus 25 via Input/Output (I/O) interfaces 22. Additionally,camera apparatus 25 in FIG. 4B may communicate with one or more externaldevices 14, including a cloud computing node 10 and/or a computersystem, and a display via Input/Output (I/O) interfaces 22.

One or more program 440 can have a set (at least one) of programmodules, and may be stored in memory 28 by way of example, and notlimitation, as well as an operating system, one or more applicationprograms, other program modules, and program data. Each of the operatingsystem, one or more application programs, other program modules, programdata, and one or more program, or some combination thereof, may includean implementation of a networking environment. One or more program 440(and optionally at least one of one or more program 441, 442, 443, 444,445) generally carry out the functions and/or methodologies ofembodiments of the invention as described herein including determiningone or more settings of a camera apparatus 96.

Referring again to FIG. 4A and FIG. 4B:

The present invention may be a system such as a computer system, amethod, and/or a computer program product. The computer program productmay include a computer readable storage medium (or media) havingcomputer readable program instructions thereon for causing a processorto carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

FIG. 5 depicts a workflow, in accordance with one or more aspects setforth herein. By way of example, the processes described with respect toFIG. 5 can be performed using one or more program 440 on one or morecomputing node 10 or one or more computing node 11 as detailed withrespect to FIGS. 1-4B.

In the embodiment of FIG. 5, one or more program 440 at block 510obtains, at one or more processor 16, one or more parameters of a cameraapparatus. One or more program 440 at block 520 determines, at one ormore processor 16, one or more settings of the camera using one or moreparameters of the camera apparatus and an image repository. The term“camera apparatus” is broadly used herein to connote any apparatuscapable of recording and/or creating images, including but not limitedto stand-alone cameras as well as camera devices integrated with mobiledevices.

FIGS. 6A-6G depict exemplary embodiments of the process depicted in FIG.5. By way of explanation, in FIGS. 6A-6G, processes are illustrated fromthe point of view of a computing node 11 one or more program 440 and acamera apparatus 25 one or more program 441. In one embodiment, one ormore program 440 runs on one or more processor of computing node 11 asfurther illustrated in the examples of FIGS. 1-4. In another embodiment,one or more program 440 runs on one or more processor of a cameraapparatus. In other embodiments, various programs can run on a differentcomplement of devices. For example, in one embodiment, one or moreprogram 440 and one or more program 441 can both run on a cameraapparatus, a computer system, or other combinations of differentdevices. FIGS. 6A and 6B illustrate processes as described, in part, inFIG. 5. FIGS. 6C-6G elaborate on FIGS. 6A and 6B, providing additionaldetailed embodiments of one or more programs 440 and/or 441. It may beunderstood that the detailed embodiments are not limiting, andadditional embodiments may include combinations of any one or more ofembodiments illustrated by FIGS. 6A-6G, as well as additionalalternative embodiments. It may also be understood that for simplicityand clarity only, FIGS. 6C-6G are based on the embodiment depicted inFIG. 6B and that each of the detailed embodiments depicted in FIGS.6C-6G may be applied to the embodiment of FIG. 6A without loss ofgenerality and without limitation.

FIG. 6A illustrates one embodiment of a process including a computingnode 11 one or more program 440 and a camera apparatus 25 one or moreprogram 441. One or more program 440 running on computing node 11 atblock 510 obtains, at one or more processor 16, one or more parameters525 a, 525 b, 525 c of camera apparatus 25. One or more program 440, atblock 520, determines one or more settings of the camera apparatus 25using the one or more parameters 525 a, 525 b, 525 c and imagerepository 550. Image repository 550 may be a part of computing node 11one or more program 440. In one example, image repository 550 mayinclude image repositories on multiple computing nodes 11 running one ormore program 440. Using one or more parameters 525 a, 525 b, 525 c ofthe camera apparatus 25 may, in one example, include camera apparatusone or more program 441 sending the one or more parameters of the cameraapparatus to computing node 11 one or more program 440. In one example,image repository 550 may be provided as a service in a cloudenvironment, as detailed with respect to FIGS. 1-4. FIG. 6A depicts oneexemplary embodiment in which image repository 550 is external from thecamera apparatus. In alternative embodiments, image repository 550 mayin part or entirely be included in camera apparatus one or more program441.

FIG. 6B illustrates another embodiment of a process including acomputing node 11 one or more program 440 and a camera apparatus 25 oneor more program 441. One or more program 440 running on computing node11 at block 510 obtains, at one or more processor 16, one or moreparameters 525 a, 525 b, 525 c of camera apparatus 25. One or moreprogram 440, at block 520, determines one or more settings of the cameraapparatus 25 using the one or more parameters 525 a, 525 b, 525 c andimage repository 550. Using image repository 550 may include one or moreprogram 441 sending a search request to computing node 11 one or moreprogram 440, and one or more program 440 may search image repository 550on computing node 11 and/or may search image repositories on multiplecomputing nodes 11 running one or more program 440. In one example,image repository 550 may be a part of computing node 11 one or moreprogram 440. In another example, image repository 550 may reside on aseparate computing node. In another example, image repository 550 mayinclude multiple image repositories computing node 11 or residing onmultiple computing nodes 11 running one or more program 440. In anotherexample, image repository 550 may be provided as a service in a cloudenvironment, as detailed with respect to FIGS. 1-4. FIG. 6B depicts oneexemplary embodiment in which image repository 550 is external from thecamera apparatus. In alternative embodiments, image repository 550 mayin part or entirely be included in camera apparatus one or more program441.

FIG. 6C illustrates one exemplary embodiment of the process of FIG. 6B.Using image repository 550 may include using one or more images 551,552, 553 of image repository 550. Image 551 may, for example, have oneor more image parameters 551 a, 551 b, 551 c, 551 d associated withimage 551. Similarly, images 552 and 553 may have one or more respectiveimage parameters associated with images 552 and 553. As FIG. 6Cillustrates, at block 555, at least one image parameter is identified ascorresponding to a parameter of the one or more parameters of the cameraapparatus. For example, camera apparatus may include camera apparatusparameters 525 a, 525 b, 525 c, and image parameter 551 c may beidentified 555 as corresponding to camera apparatus parameter 525 c. Forinstance, camera apparatus parameter 525 c may be a shutter speed of thecamera apparatus, and image parameter 551 c may correspond to theshutter speed of a camera that was used to create image 551. Similarly,in another instance, camera apparatus parameter 525 c might correspondto a condition external to the camera apparatus, such as an ambientlighting condition, and image parameter 551 c may correspond to the sameexternal condition, such as the ambient lighting condition in whichimage 551 was created.

As FIG. 6C indicates, one or more images 551, 552, 553 need not have thesame image parameters or the same number of image parameters. As well,any two or more images 551, 552 may have similar types of imageparameters 551 c, 551 c, 552 c, but specific values for image parametersof one image may not correspond to camera apparatus parameters. Forexample, image parameters 551 c, 552 c and camera apparatus parameter525 c may be ambient light condition parameters. Camera apparatusparameter 525 c may more specifically be a low lighting condition, suchas when a user is using the camera apparatus indoors in dim lighting.Image parameter 551 c may be a similar or matching low lightingcondition, as image 551 may have been created by a camera that wasindoors and in dim lighting, and thus may be identified as correspondingto camera apparatus parameter 525 c. Image parameter 552 c, on the otherhand, may specifically be a bright lighting condition, as image 552 mayhave been created by a camera that was outdoors in bright sunlight, andthus may not be identified as corresponding to camera apparatusparameter 525 c even though both image parameter 552 c and cameraapparatus parameter 525 c are generally “ambient lighting condition”parameters.

FIG. 6D further details the processes illustrated by FIGS. 6B and 6C. Inone embodiment, the one or more images 551, 552, 553 of image repository550 may have a respective rating attribute 551 e, 552 e, 553 e, as wellas one or more image parameters. A rating attribute may correspond, forexample, to numerical ratings given to an image by users of imagerepository 550 and/or to an average or aggregate rating of numericalratings given to the image by users of image repository 550. Forinstance, images in image repository 550 may be presented to users via aweb-site, a computer program product, as part of a service provided in acloud environment, or by another means of presenting images. Users maybe allowed to, for example, assign a numerical rating to an image,approve or disapprove an image, and so on. Users may assign high ratingsto images for any reason or several reasons, such as pleasing aestheticqualities of an image, interesting subject matter of an image, technicalqualities of an image, and so on. Conversely, users may give low ratingsto images that, for example, have poor technical qualities,uninteresting subject matter, and so on. As detailed further below,using rating attributes associated with images in image repository 550may facilitate using images of the image repository 550 to determine oneor more settings of a camera apparatus, as an image with a high ratingattribute may be very likely to be a high-quality image created withappropriate or optimal camera settings.

As illustrated in FIG. 6D, the process may include, at block 560,identifying at least one image of the one or more images to be includedin a subset of images 570, wherein the identifying is based on therating attribute of the at least one image and on at least one imageparameter of the at least one image. In the example specificallydepicted in FIG. 6D, images 551 and 552 are identified 560 to beincluded in subset of images 570, based on at least one image parameterof image 551 and at least one image parameter of image 552 and therespective rating attributes 551 e, 552 e, as further illustrated anddetailed in FIG. 6E. Identifying 560 at least one image to be includedin subset of images 570 may further include using the one or moreparameters of the camera apparatus 25, as correlations between imageparameters and camera apparatus parameters may be used to identify whichimages 551, 552 of image repository 550 are to be included in subset ofimages 570 and which images, such as image 553, should not be includedin subset of images 570, as also further illustrated in FIG. 6E.

FIG. 6E depicts a portion of FIG. 6D in detail to further illustrateidentifying 560 at least one image to include in subset of images 570.For example, identifying 560 the at least one image 551 to be includedin the subset of images 570 may involve identifying 555 an image 551that has more image parameters 551 a, 551 b, 551 d that correspond toparameters 525 a, 525 b, 525 d of the one or more parameters of thecamera apparatus 25 than images of the one or more images, such as image553, not identified to be included in the subset of images 570. As theexample of FIG. 6E illustrates, identifying 560 at least one image mayinclude identifying additional images, such as image 552, to be includedin subset of images 570. As further illustrated by FIG. 6E, imageparameters 551 a, 551 b, 551 d of image 551 are identified ascorresponding to parameters 525 a, 525 b, 525 d of the one or morecamera apparatus parameters, while image parameters 552 a, 552 b, 552 cof image 552 are identified as corresponding to parameters 525 a, 525 b,525 c of the one or more camera apparatus parameters. Thus, images 551,552 included in subset of images 570 need not share identical imageparameters that correlate to the one or more parameters of the cameraapparatus. For instance, images 551 and 552 of subset of images 570 mayshare similar image parameters 551 a, 552 a such as a model of cameraused to create images 551 and 552, which may correspond to, by way ofexample, a camera model parameter 525 a of the camera apparatus. On theother hand, image 551 may have, by way of example, a lighting conditionparameter 551 c corresponding to bright lighting and image 552 may havea lighting condition parameter 552 c corresponding to dim lighting; ifcamera apparatus has a camera apparatus parameter 525 c corresponding todim lighting, then image parameter 552 c may correlate to cameraapparatus parameter 525 c while image parameter 551 c may not.Similarly, by way of example, image 551 may have an image parameter 551d that corresponds to a camera apparatus parameter 525 d, but image 552may lack a similar image parameter. For instance, image 552 may not haveany information regarding weather conditions associated with image 552.

The examples of correlation between image parameters and cameraapparatus parameters illustrated by FIG. 6E and described above are byway of illustration and example only, and it should be apparent thatimages included in subset of images 570 may have many more correlationsbetween associated image parameters and camera apparatus parameters, ormay have fewer such correlations. Generally, at least one image 551included in subset of images 570 will have at least one image parameter,such as image parameter 551 a, that correlates with at least oneparameter 525 a of the one or more camera apparatus parameters. It ispossible, in some embodiments, for no images of image repository 550 tobe identified to be included in subset of images 570, as it is possiblethat no image in image repository 550 has any image parameters thatcorrespond to any parameters of the one or more camera apparatusparameters. In this case, one or more program 440 and/or one or moreprogram 441 may revert determination of the one or more settings of thecamera apparatus to the camera apparatus and/or the user of the cameraapparatus.

As further illustrated in FIG. 6E, at least one image 551 identified 560to be included in subset of images 570 may have a higher ratingattribute 551 e than images of the one or more images, such as image553, not identified to be included in the subset of images. A ratingattribute may correspond, for example, to numerical ratings given to animage 551, 552, 553 by users of image repository 550 and/or to anaverage or aggregate rating of numerical ratings given to the image byusers of image repository 550. The rating attribute 551 e of an image551 in image repository 550 may be significant in identifying 560 theimage to be included in subset of images 570 or to not be included insubset of images 570, as it may generally be desirable to include imageswith high rating attributes in the subset of images 570 and to notinclude images with low rating attributes. Although rating attributesmay be assigned by users of image repository 550 for subjective or evenarbitrary reasons, users may generally assign a high rating attribute toan image if it is, for example, aesthetically pleasing and/or visuallyappealing, or if it exemplifies certain technical qualities, forinstance. Images with a high rating attribute, for example a highaverage rating of numerous individual ratings, are likely to be imagescreated with the most appropriate camera apparatus settings, such asclose-up images created with an appropriate lens type and correct focallength, images of subjects in motion created with the most appropriateshutter speed, images created indoors with the most appropriate flashsettings, and so on. Images with a low rating attribute, on the otherhand, are likely to be images created with one or more incorrect orinappropriate camera apparatus settings. For example, an image mayreceive a low average rating if the image was created in dim lightingwithout use of a flash, or if, in another example, the image is of asubject in motion taken at too low of a shutter speed, resulting in ablurry image. Taking a rating attribute 551 e of an image 551 intoaccount when identifying 560 at least one image may help ensure thatimages selected to be included in the subset of images 570 may be thebest or most appropriate images for determining the one or more settingsof the camera apparatus, as described further below.

As shown in FIG. 6E, an image 553 of image repository 550 may not beidentified for inclusion in subset of images 570. Image 553, forexample, may have a relatively low rating attribute 553 e, so that evenif image 553 has several image attributes 553 a-553 c that correlate tothe one or more camera apparatus parameters 525 a-525 c, the image willnot be identified for inclusion in the subset of images. As well, oralternatively, image 553 may have few or no image parameters 553 a, 553b that can be identified 555 as corresponding with any of the one ormore parameters of the camera apparatus. As depicted in the example ofFIG. 6E, image 553 may have one or more image parameters 553 c thatcorrespond to a parameter 525 c of the one or more camera apparatusparameters; however, the identifying 560 by one or more program 440and/or one or more program 441 may determine that the correlationbetween image parameter 553 c and camera apparatus parameter 525 c isnot sufficient to include image 553 in subset of images 570. Thus, it ispossible that an image 553 of image repository 550 may have a higherrating attribute 553 e than another image 551 of image repository 550,but image 553 may not be included in subset of images 570 if it has fewor no image parameters that can be identified as corresponding with theone or more camera apparatus parameters. For example, the image 553 maybe very highly rated but may be inappropriate for determining one ormore settings of the camera apparatus because image 553 was created, forinstance, by a digital single-lens reflex (DSLR) camera with a zoom lenswhereas the camera apparatus is a low-resolution camera of a mobiledevice without a zoom lens. In an alternative embodiment, even onecorrelation between an image parameter 553 c and camera apparatusparameter 525 c may allow for inclusion in subset of images 570.

In one example embodiment, the identifying 560 may include apre-selected minimum number of image parameters that any image of imagerepository 550 must have that correlate with the one or more cameraapparatus parameters in order for the image to be included in the subsetof images. In another example, the identifying 560 may “on the fly”determine how many image parameters of an image should correlate to theone or more camera apparatus parameters in order for the image to beincluded in the subset of images 570. This may, for example, allow oneor more program 440 and/or one or more program 441 a great deal offlexibility in the identifying 560 of images, as in some cases imagerepository 550 may only have images that have just a few or even onlyone image parameter that correlate to camera apparatus parameters, andin other cases image repository 550 may have several images with fewcorrelations between the image parameters and camera apparatusparameters as well as several images with a high number of correlationsbetween the image parameters and camera apparatus parameters.

In yet another alternative embodiment, some image parameters may beweighted more highly than other image parameters, so that images 551,552 included in the subset of parameters may have image parameters thatcorrelate to more significant camera apparatus parameters. For example,it may be more important to identify images of image repository 550 thatwere created with a particular type of lens, such as a wide-angle lensor zoom lens, than it is to identify images of image repository 550 thatwere created with the same model or brand of camera. In this example, animage parameter for “lens type” may be weighted more heavily, such as bya numerical weight value, than an image parameter for “camera model,” sothat an image is more likely to be identified 560 for inclusion in thesubset of images 570 if the image has a “lens type” image parameter thatcorrelates to a “lens type” parameter of the camera apparatus, even ifthe image does not have a “camera model” parameter that correlates tothe “camera model” parameter of the camera apparatus. Similarly, animage in image repository 550 that has a “lens type” image parameterthat does not correlate to the “lens type” parameter of the cameraapparatus may be less likely to be included in subset of images 570,even if the image has a “camera model” parameter that correlates exactlyto the “camera model” parameter of the camera apparatus.

It may be understood that the several variant embodiments describedabove are not exhaustive, and it may be further understood that otherparameters or conditions may also or alternatively be used inidentifying 560 one or more images of an image repository 550 to beincluded in the subset of images 570.

FIG. 6F further depicts the process of FIGS. 6B-6E, in which the one ormore images of image repository 550 have one or more camera settingsassociated with the one or more images, such as the camera settings 552f, 552 g, 552 h associated with image 552. The camera settings 552 f,552 g, 552 h of an image 552 may correspond to camera settings that wereused to create the image 552. Determining the one or more settings forthe camera apparatus may further include, at block 580 of one or moreprogram 440, selecting one image 552 of subset of images 570. The oneimage 552 may have a higher rating attribute than the rating attributesof other images 551 in the subset of images 570. It may be understoodthat block 580 is depicted in FIG. 6F as being carried out by one ormore program 441 for simplicity, and that block 580 may alternatively becarried out by one or more program 440 running on computing node 11, ormay be carried out in part by one or more program 440 and in part by oneor more program 441.

Determining the one or more settings for the camera apparatus may alsoinclude, at block 590, automatically adjusting the one or more settingsfor the camera apparatus 25 based on the one or more camera settings 552f, 552 g, 552 h associated with the one image 552. As depicted in theexample of FIG. 6F, block 590 may be carried out at camera apparatus 25one or more program 441. It may be understood that in other exampleembodiments, block 590 may be carried out in part by one or more program441 running on the camera apparatus 25 and in part by one or moreprogram 440 running on computing node 11. For example, one or moreprogram 440 may send camera settings 552 f, 552 g, 552 h of selectedimage 552 to the camera apparatus one or more program 441, and one ormore program 441 may use camera settings 552 f, 552 g, 552 h toautomatically adjust similar or corresponding settings of the cameraapparatus. For instance, camera settings 552 f, 552 g, 552 h may berespectively a focal length setting, a flash setting, and a shutterspeed setting, that were used to create image 552. At block 590, one ormore program 441 and/or one or more program 440 may automatically adjustthe focal length setting, flash setting, and shutter speed setting ofthe camera apparatus. It may be understood that camera settings 552 f,552 g, 552 h are depicted in FIG. 6F by way of example only, and that animage selected at block 580 may have more or fewer camera settings,and/or different camera settings, associated with the selected image.

FIG. 6G further depicts the process of FIGS. 6B-6E in an alternativeembodiment, in which subset of images 570, at block 575, are displayedat the camera apparatus 25. At block 580, one image 551 of the subset ofimages 570 is selected. In exemplary embodiments, selecting 580 an image551 may be performed by a user of the camera apparatus 25, based on thedisplay of the subset of images 575. For example, one or more program441 may obtain subset of images 570 and display 575 the images, forexample, on a display screen or in a user interface that may allow theuser to select one image of the subset of images 570. In such anexample, the user may be able to view the images included in the subsetof images 570, and may be able to select, via a user interface, oneimage 551 of the subset of images 570. The camera settings 551 f, 551 g,551 h associated with the image 551 selected by the user may then beused to automatically adjust, at block 590, the one or more settings ofthe camera apparatus.

In any one or more of the embodiments of FIGS. 5 and 6A-6G, or inalternative embodiments, the one or more settings of the cameraapparatus may include, but are not limited to, one or more of a focallength, a shutter speed, an exposure time, a color balance, a flashsetting, a light sensitivity setting, or an aperture size. In any one ormore of the embodiments of FIGS. 5 and 6A-6G, or in alternativeembodiments, the one or more parameters of the camera apparatus mayinclude, but are not limited to, one or more of a camera brand, a cameramodel, an image resolution, a pixel size, a geographical location, alighting condition, a weather condition, a date parameter, a timeparameter, a camera orientation parameter, a focal length, a shutterspeed, an exposure time, a color balance, a flash setting, a lightsensitivity setting, or an aperture size.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willbe further understood that the terms “comprise” (and any form ofcomprise, such as “comprises” and “comprising”), “have” (and any form ofhave, such as “has” and “having”), “include” (and any form of include,such as “includes” and “including”), and “contain” (and any form ofcontain, such as “contains” and “containing”) are open-ended linkingverbs. As a result, a method or device that “comprises,” “has,”“includes,” or “contains” one or more steps or elements possesses thoseone or more steps or elements, but is not limited to possessing onlythose one or more steps or elements. Likewise, a step of a method or anelement of a device that “comprises,” “has,” “includes,” or “contains”one or more features possesses those one or more features, but is notlimited to possessing only those one or more features. Furthermore, adevice or structure that is configured in a certain way is configured inat least that way, but may also be configured in ways that are notlisted. It will be further understood that the term “based on” isintended to include both “based on in part” and “based on entirely” or“entirely based on.”

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below, if any, areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description set forth herein has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the disclosure. Theembodiment was chosen and described in order to best explain theprinciples of one or more aspects set forth herein and the practicalapplication, and to enable others of ordinary skill in the art tounderstand one or more aspects as described herein for variousembodiments with various modifications as are suited to the particularuse contemplated.

What is claimed is:
 1. A method comprising: obtaining, with use of oneor more processor, one or more parameters of a camera apparatus; anddetermining, with use of the one or more processor, one or more settingsfor the camera apparatus using the one or more parameters of the cameraapparatus and one or more images of an image repository, the one or moreimages having one or more image parameters associated with the one ormore images, wherein the determining comprises identifying, with use ofthe one or more processor, a correspondence between at least one imageparameter and at least one parameter of the one or more parameters ofthe camera apparatus, and wherein the one or more images have respectiveuser rating attributes provided by one or more users of the imagerepository, wherein the using the one or more images of the imagerepository comprises identifying at least one image of the one or moreimages to be included in a subset of images, and wherein the identifyingis based on the user rating attribute of the at least one image and onat least one image parameter of the at least one image.
 2. The method ofclaim 1, wherein the at least one image identified to be included in thesubset of images has more image parameters identified as correspondingto parameters of the one or more parameters of the camera apparatus thanimages of the one or more images not identified to be included in thesubset of images.
 3. The method of claim 1, wherein the at least oneimage identified to be included in the subset of images has a higheruser rating attribute than images of the one or more images notidentified to be included in the subset of images.
 4. The method ofclaim 1, wherein the one or more images have one or more camera settingsassociated with the one or more images, the camera settings of one imagecorresponding to camera settings used to create the one image, andwherein determining the one or more settings for the camera apparatusfurther comprises: selecting one image of the subset of images, andautomatically adjusting the one or more settings for the cameraapparatus based on the one or more camera settings associated with theone image.
 5. The method of claim 4, wherein the one image has a higheruser rating attribute than user rating attributes of other imagesincluded in the subset of images.
 6. The method of claim 4, furthercomprising displaying the subset of images at the camera apparatus, andwherein selecting one image of the subset of images is performed by acamera apparatus user of the camera apparatus based on the display ofthe subset of images.
 7. The method of claim 1, wherein the one or moresettings of the camera apparatus comprise one or more of a focal length,a shutter speed, an exposure time, a color balance, a flash setting, alight sensitivity setting, or an aperture size.
 8. The method of claim1, wherein the one or more parameters of the camera apparatus compriseone or more of a camera brand, a camera model, an image resolution, apixel size, a geographical location, a lighting condition, a weathercondition, a date parameter, a time parameter, a camera orientationparameter, a focal length, a shutter speed, an exposure time, a colorbalance, a flash setting, a light sensitivity setting, or an aperturesize.
 9. The method of claim 1, wherein the image repository is providedas a service in a cloud environment.
 10. The method of claim 1, whereinthe method includes providing a user interface that allows users of theimage repository to assign the respective user rating attributes to theone or more images.
 11. The method of claim 1, wherein the methodincludes providing a user interface that allows users of the imagerepository to assign the respective user rating attributes to the one ormore images. and wherein the respective user rating attributes of theone or more images provided by one or more users of the image repositoryinclude averages or aggregates of numerical ratings assigned to therespective one or more images by the one or more users of the imagerepository.
 12. The method of claim 1, wherein the method includesdisplaying a displayed interface that displays the subset of images andfacilitates selecting of one image of the subset of images by a certainuser, and automatically adjusting the one or more settings for thecamera apparatus based on one or more camera settings associated withthe one image.
 13. A computer program product comprising: a computerreadable storage medium readable by one or more processing circuit andstoring instructions for execution by one or more processor forperforming a method comprising: obtaining one or more parameters of acamera apparatus; and determining one or more settings for the cameraapparatus using the one or more parameters of the camera apparatus andone or more images of an image repository, the one or more images havingone or more image parameters associated with the one or more images,wherein the determining comprises identifying a correspondence betweenat least one image parameter and at least one parameter of the one ormore parameters of the camera apparatus, and wherein the one or moreimages have respective user rating attributes provided by one or moreusers of the image repository, wherein the using the one or more imagesof the image repository comprises identifying at least one image of theone or more images to be included in a subset of images, and wherein theidentifying is based on the user rating attribute of the at least oneimage and on at least one image parameter of the at least one image. 14.The computer program product of claim 13, wherein the one or more imageshave one or more camera settings associated with the one or more images,the camera settings of one image corresponding to camera settings usedto create the one image, and wherein determining the one or moresettings for the camera apparatus further comprises: selecting one imageof the subset of images, and automatically adjusting the one or moresettings for the camera apparatus based on the one or more camerasettings associated with the one image.
 15. The computer program productof claim 14, wherein the one image has a higher user rating attributethan user rating attributes of other images included in the subset ofimages.
 16. The computer program product of claim 14, further comprisingdisplaying the subset of images at the camera apparatus, and whereinselecting one image of the subset of images is performed by a cameraapparatus user of the camera apparatus based on the display of thesubset of images.
 17. The computer program product of claim 14, whereinthe one or more settings of the camera apparatus comprise a focallength, a shutter speed, an exposure time, a color balance, a flashsetting, a light sensitivity setting, and an aperture size.
 18. Thecomputer program product of claim 14, wherein the one or more parametersof the camera apparatus comprise a camera brand, a camera model, animage resolution, a pixel size, a geographical location, a lightingcondition, a weather condition, a date parameter, a time parameter, acamera orientation parameter, a focal length, a shutter speed, anexposure time, a color balance, a flash setting, a light sensitivitysetting, and an aperture size.
 19. The computer program product of claim14, wherein the method includes providing a user interface that allowsusers of the image repository to assign the respective user ratingattributes to the one or more images. and wherein the respective userrating attributes of the one or more images provided by one or moreusers of the image repository include averages or aggregates ofnumerical ratings assigned to the respective one or more images by theone or more users of the image repository, and wherein the methodincludes displaying a displayed interface that displays the subset ofimages and facilitates selecting of one image of the subset of images bya certain user, and automatically adjusting the one or more settings forthe camera apparatus based on one or more camera settings associatedwith the one image.
 20. A system comprising: a memory; one or moreprocessor in communication with the memory; program instructionsexecutable by the one or more processor via the memory to perform amethod comprising: obtaining one or more parameters of a cameraapparatus; and determining one or more settings for the camera apparatususing the one or more parameters of the camera apparatus and one or moreimages of an image repository, the one or more images having one or moreimage parameters associated with the one or more images, wherein thedetermining comprises identifying a correspondence between at least oneimage parameter and at least one parameter of the one or more parametersof the camera apparatus, and wherein the one or more images haverespective user rating attributes provided by one or more users of theimage repository, wherein the using the one or more images of the imagerepository comprises identifying at least one image of the one or moreimages to be included in a subset of images, and wherein the identifyingis based on the user rating attribute of the at least one image and onat least one image parameter of the at least one image.